Course: Optimization problems

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Course title Optimization problems
Course code NTI/OPT
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 2
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Šembera Jan, doc. Ing. Ph.D.
Course content
Lectures: 1. Numerical methods of looking for extremals of functions, minimization of a function of one variable (Fibonacci method and the golden section method) and Newton Raphson method 2.-3. Minimization of a function of more variables without restrictions: Nelder-Mead method, gradient methods, conjugate gradient method. 4.-5. Minimization of a function of more variables with equality constraints: Lagrange multiplicator method 6.-7. Minimization of a function of more variables with inequality constraints (mathematical programming): formulation of the problem for Matlab, derivation of Kuhn-Tucker conditions. The tutorials are led in a computer room using the MATLAB software.

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing)
Learning outcomes
The course develops the students' knowledge in the field of basic methods of optimization problem solution. It connects the theoretical lecture with solution of specific practical problems using the MATLAB software. After the course, the student is able to choose a proper
After the course, the student is able to choose a proper method for solution of his optimization problem and propose the corresponding algorithm in the MATLAB SW.
Prerequisites
Unspecified

Assessment methods and criteria
Written exam

Requirements for getting a credit are activity at the seminars and successful passing the tests
Recommended literature
  • R.FLETCHER. Practical methods of optimization.. 1987. ISBN ISBN 0-471-91547-.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Mechatronics, Informatics and Interdisciplinary Studies Study plan (Version): Applied Sciences in Engineering (2019) Category: Special and interdisciplinary fields 3 Recommended year of study:3, Recommended semester: Winter
Faculty: Faculty of Mechatronics, Informatics and Interdisciplinary Studies Study plan (Version): Applied Sciences in Engineering (2016) Category: Special and interdisciplinary fields 3 Recommended year of study:3, Recommended semester: Winter